Statistical Measures.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean : 5.843333333333335 \n",
      "Median : 5.8\n",
      "Variance : 0.6811222222222222 \n",
      "Median Absolute Deviaton : 1.0378215529539216\n"
     ]
    },
    {
     "data": {
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X6FX1+qraXlULLP/q9bGq+qGfgEPn+C4EDmxgxIcynJLk0Q89Bl4E3Dk07AbgVwbvJDib5V/P7p21nEke/9A5viTPZfn76psbmROgqr4OfCXJmYNNO4DPDg2b+pyOknNW5nTgEo5/CmPq8znkuFlnZE7vAc5OsnWQZQcP758bgMsGj1/KcoeNtELvdKXoZpLkD4H9VXUD8KokFwJHWf7Jd/kUIj0OeP/g+2sL8O6q+kiSXweoqrexfBXui4G7ge8AL5vRnC8FXpnkKPC/wMWjfgOugyuAawe/en8ReNkMzukoOWdiTpNsBc4Hfu2YbbM4n6NknfqcVtW+JHtZPv1zFLgd2DPUT1cBf5Pkbpb76eJRX98rRSWpEc2dcpGkE5WFLkmNsNAlqREWuiQ1wkKXpEZY6JLUCAtdkhphoUtSI/4PHRL9g6QKC1IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Statistical Measures\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from statsmodels import robust as rb\n",
    "import matplotlib.pyplot as mtp\n",
    "\n",
    "irisData = pd.read_csv('Datasets/IRIS.csv')\n",
    "\n",
    "meanVal = np.mean(irisData[\"sepal_length\"])\n",
    "medianVal = np.median(irisData[\"sepal_length\"])\n",
    "variance = np.var(irisData[\"sepal_length\"])\n",
    "madVal = rb.mad(irisData[\"sepal_length\"])\n",
    "print(\"Mean : {} \\nMedian : {}\\nVariance : {} \\nMedian Absolute Deviaton : {}\".format(meanVal, medianVal, variance, madVal))\n",
    "mtp.hist(irisData[\"sepal_length\"], 20)\n",
    "mtp.show()"
   ]
  }
 ],
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